Sophisticated analysis of imaging data requires software that can rapidly identify meaningful regions of the image. Depending on the size and number of regions, this process may require evaluating very large datasets, and thus efficient sorting of the data is essential for finding the desirable elements. In the present invention, regions of interest (ROIs) in previous feature-based imaging spectroscopy are extended to include pixel-based analyses. This requires new algorithms, since the size of a pixel-based analysis can be more than 1000 times larger than that of a feature-based analysis. In addition to requiring a burdensome amount of processing time, prior art sorting algorithms that may have been adequate to categorize and classify relatively noiseless feature data are not necessarily successful in sorting single-pixel spectra without additional parameters or human intervention.
In cases in which human intervention is advantageous, the present invention includes a means for combining machine and human intelligence to enhance image analysis. For example, the present invention provides a method for combining sorting by spectral criteria (e.g., intensity at a given wavelength) and sorting by temporal criteria (e.g., absorbance at a given time). Sorting enables the user to classify large amounts of data into meaningful and manageable groups according to defined criteria. The present invention also allows for multiple rounds of pixel or feature selection based on independent sorting criteria. Methods are presented for extracting useful information by combining the analyses of multiple datasets and datatypes (e.g., absorbance, fluorescence, or time), such as those obtained using the instruments and methods disclosed in U.S. Pat. Nos. 5,859,700 and 5,914,245, and in U.S. patent application Ser. No. 09/092,316.
The methods described herein are useful for a number of applications in biology, chemistry and medicine. Biomedical applications include high-throughput screening (e.g., pharmaceutical screening) and medical imaging and diagnostics (e.g., oximetry or retinal examination). Biological targets include live or dead biological cells (e.g., bacterial colonies or tissue samples), as well as cell extracts, DNA or protein samples, and the like. Sample formats for presenting the targets include microplates and other miniaturized assay plates, membranes, electrophoresis gels, microarrays, macroarrays, capillaries, beads and particles, gel microdroplets, microfluidic chips and other microchips, and compact discs. More generally, the methods of the present invention can be used for analysis of polymers, optical materials, electronic components, thin films, coatings, combinatorial chemical libraries, paper, food, packaging, textiles, water quality, mineralogy, printing and lithography, artwork, documents, remote sensing data, computer graphics and databases, or any other endeavor or field of study that generates multidimensional data.